During the last decade, significant advances have been made in the area of statistical demography. In particular, new methodologies have been developed for probabilistic population projections. The United Nations have adopted many of them for their World Population Prospects, in which their official population projections are issued for all countries of the world. Methods for projections at the subnational level are starting to be adopted by national and local statistical offices for their official population forecasts.
Currently, the methodology is spread out across a large number of publications and it is difficult, especially for practitioners, to learn it in the absence of a concise source. Thus, this project is designed to compile and organize the science in one place, so that the resulting book will facilitate cross-disciplinary understanding and accessibility. During the fellowship I plan to contribute to the chapters on Bayesian Population Forecasting, which will form the core of the book.
Several methodological challenges in probabilistic population projections remain to be solved. A STIAS fellowship would also provide me with the opportunity to focus on the issue of forecasting net migration by sex and age. This is not yet fully solved, and is vital for the production of good population projections, as migration has become one of the most important components of population change around the world.
The project is highly innovative and interdisciplinary, as demographic projections have implications for many other scientific areas, such as climate science, global health, food security, and urban planning.